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Do you agree with the AI automation risk score calculated for this occupation?
AI Automation Index
Task-level automation exposure for Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders: 11 O*NET tasks scored against their work activities, plus the simulator.
Automation Exposure
11 of 11 tasks scored
Median Salary
BLS OEWS, May 2025 — this exact occupation
Employment Level
14,760 people hold this job — size, not growth
Projected 2025–35
1,700 openings a year · BLS line item
BLS OEWS publishes 40 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$22,620 – $64,610
Highest medians
Lowest medians
State figures come from the 51-9192 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Importance-weighted mean of the scored tasks. This is the headline index.
Share of weighted tasks in hands-on or machine-operating work activities.
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Share in documenting, recording, and administrative activities.
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
11 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
1 tasks
0 tasks
10 tasks
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Add specified amounts of chemicals to equipment at required times to maintain solution levels and concentrations.
physical manipulation — Applying solutions to equipment is manual
Observe machine operations, gauges, or thermometers, and adjust controls to maintain specified conditions.
visual inspection — Instrument monitoring needs physical sensor presence
Set controls to regulate temperature and length of cycles, and start conveyors, pumps, agitators, and machines.
physical manipulation — Manual temperature control adjustment
Drain, clean, and refill machines or tanks at designated intervals, using cleaning solutions or water.
physical manipulation — Hands-on cleaning of equipment in unstructured settings
Operate or tend machines to wash and remove impurities from items such as barrels or kegs, glass products, tin plate surfaces, dried fruit, pulp, animal stock, coal, manufactured articles, plastic, or rubber.
physical manipulation — Hands-on control of industrial machinery in unstructured settings
Record gauge readings, materials used, processing times, or test results in production logs.
data analysis — Record production data into structured logs
Examine and inspect machines to detect malfunctions.
visual inspection — Physical inspection of production machinery in situ
Measure, weigh, or mix cleaning solutions, using measuring tanks, calibrated rods or suction tubes.
physical manipulation — Physical measuring and dispensing of ingredients
Draw samples for laboratory analysis, or test solutions for conformance to specifications, such as acidity or specific gravity.
physical manipulation — Chemical/physical testing requires lab manipulation
Adjust, clean, and lubricate mechanical parts of machines, using hand tools and grease guns.
physical manipulation — Manual lubrication of production equipment
Load machines with objects to be processed and unload them after cleaning, placing them on conveyors or racks.
physical manipulation — Physically extracting parts from production equipment
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<script src="https://giniloh.com/embed.js" async></script> Community Sentiment
Do you agree with the AI automation risk score calculated for this occupation?
Method
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
See the full method →Related Article
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